SNP Copy Number and Loss of Heterozygosity Estimation

protocols

Compute SNP copy number and loss of heterozygosity (LOH) based on Affymetrix SNP chip data for paired target/normal samples. In cancer genomics, copy number change is one of the hallmarks of the genetic instability common to most human cancers and LOH of tumor suppressor genes is a crucial step in the development of sporadic and hereditary cancer (Monti, 2005).

Before You Begin

learn more:
file formats

Step 1: SNPFileCreator

SNPFileCreator converts the CEL files from an array into a GenePattern .snp file. Raw data for the probes in each SNP probe set are converted to a single intensity value per SNP using one of four modeling algorithms: Average Difference, PM/MM Difference Model (dChip, the default), Median Probe, or Trimmed Mean.

20-30 minutes: Processing this example on the GenePattern public server takes time. The example source data and resulting SNP file are provided here for your convenience: GISTIC_Hind_subset.zip, GISTIC_Hind_subset.snp.

Considerations
learn more:
SNPFileCreator

Step 2: XChromosomeCorrect

For gender-specific samples, run the XChromosomeCorrect module to correct intensity values for SNPs on the X chromosome. For each sample from a male donor, the module doubles the intensity value for SNPs on the X chromosome.

The sample information file must include a column labeled Gender that contains a value of M or F for each sample.

learn more:
XChromosomeCorrect

Step 3: CopyNumberDivideByNormals

CopyNumberDivideByNormals computes the raw copy number of each target SNP by dividing its intensity value by the mean intensity value of all normal SNPs. This calculation is referred to as copy number normalization or normalization with respect to normals.

CopyNumberDivideByNormals creates one of two files:

learn more:
CopyNumberDivideByNormals

Step 4: IGV

The Integrative Genomics Viewer (IGV) is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations. By default, IGV displays all chromosomes. To zoom in on a chromosome, select it from the chromosome tool bar.

learn more:
IGV

Reference

Monti, S. 2005. Class slides: SNP microarrays and high-density genotyping. http://www.chip.org/teaching/hst950/slides/class6.pdf.